... however, the more you know, the more in awe you become at your own ignorance! "...those who feel certainty are stupid, and those with any imagination and understanding are filled with doubt and indecision." --Bertrand Russel

Wednesday, November 16, 2011

A few weeks ago I was asked to discuss how it seems that retailers are putting out Christmas items earlier and earlier each year by a local TV station, and by Matt Small at AP Radio. Of course, the press often chooses one small, silly point you make to include for your 5 seconds of fame. My better points about the situation were:

Reasons why it happens:
This is a general case of a "prisoner's dilemma" or "race to the bottom". Stores believe that if they don't do it, everyone else will, and they will lose out. They also believe that even if everyone else doesn't, they will win by being first. We are seeing the same kind of leap-frogging in the presidential primaries-- we all agree that this is the wrong outcome, but individual, selfish behavior makes it rational for individuals, but irrational for the collective result. By the way, consumers are just as much to blame- enough of us play the game and will show up whenever the stores tell us we might get a good deal and save $20-- even if that means freezing and getting sick at 3am rather than snoozing in your nice, warm bed. Not me, however-- but if you see a good deal, grab me one since you're already there. ☺

Additionally, since the Christmas season accounts for as much as 40% of yearly sales, retailers make sure to order their merchandise well ahead of time, so that there are no supply-chain mix-ups. I believe that this adds pressure as well. If you have the merchandise on hand, why not put it out?

Reasons why it is a bad idea
However, there are a few reasons why I think that this trend is a bad idea. First, I don't really believe that putting Christmas items out for twice as long will lead to twice as much spending. Plus, all of that Christmas merch takes up a lot of space-- there are lots of things that I'd like to buy that stores won't be carrying this week, because of all of the Christmas stuff they have out. A concrete example is that Walmart clears out most of their garden section for their Christmas items-- they do this so early now that you can't buy supplies for your Fall lime/seeding that one does in order to hope for a few blades of grass to grow the following year.

Secondly, as this NY Times article mentions, some retailers are thinking of opening just a little earlier for Black Friday-- Target, Khols, and others on Midnight Thanksgiving. Walmart has one-upped them by saying that they will open at 10PM on Thanksgiving. In some people's opinions, this is a bad idea. I agree! Why? Sadly, the best answer I can give is that it violates my sense of tradition. Christmas largely has its power in today's secular west because of "Christmas Traditions", after all. Black Friday has become a tradition, as well, and I firmly believe that forcing people out of stores, and giving an almost universal day off for Thanksgiving is an important part of the season. Pretty soon, Thanksgiving and Black Friday will both seem like "just another day"-- how long will it be before Christmas is just another workday, as well? (And then where will 40% of your revenues come from, eh Walmart?)

Cheers-
-Dr. B

PS: Another interesting issue I'd like to know about is, with Christmas goods out for so long, how do prices fluctuate during the season? Economists often discuss this issue in terms of the so-called "Durable Goods Problem". This phenomenon suggests that we all know that producers and sellers often charge higher prices for goods when they are first put out, but lower prices later if you wait. Think of iPhones, day after Christmas sales, the latest model of car, computer, or clothes. The simplistic version of the durable goods problem suggests that this won't work if everyone is rational, because we will ALL wait instead of paying the high price today. In reality, there are (at least) three types of people: Early adopters, "normal" people, and budget-conscious planners. So, some people get a thrill from blowing their money on the latest gadget, some buy it after the first price drop, and some people buy the used, older version from the early adopters on Craigslist! Long story short, I wonder if prices on Christmas goods follow this same pattern?

First, the numbers between the CEW and WSJ sites do not match up.The WSJ Numbers were different because they were based on 2010 ACS Survey data rather than 2009 ACS data.

Second, the WSJ says that the data used is from the 2010 US Census, which has to be false. The Census Bureau did not collect any data on earnings or education in the 2010 Census. Yes, they used to, and their failure to collect this data in 2010 will be seen as a huge mistake in the future, because small area studies relying on Census data can no longer be done. By small I mean the Census Tract or Block Group Level. In any case, the study used the 2009 "American Community Survey", which is administered by the Census Bureau.As above, they used 2010 ACS data, which should be carefully distinguished from 2010 Census Data.

Third, and most important, is that no effort is made to express the accuracy of these numbers. Let me demonstrate why this is so important. In order to demonstrate this, I am relying on combining two sources: The data at the CEW, and also a table from the ACS 2009 with summary statistics AND margins of error. Here is a link to it, but be forewarned it is pretty big. According to the 2009 ACS, 35,494,367 (+/- 120,221) people in the US have a 4 year degree as their highest education level, out of 201,952,383 people over 25 years old. Looking here at computers/math majors in the CEW report, they say that 7,829 (+/- not given) people have degrees in "Math and Computer Science" (I am assuming a double major?).

Here comes my point: The ACS in 2009 surveyed 1,917,748 households, and let us suppose that translates into around 3,000,000 people who are 25 and older (around 1.5 people over 25 per household). That means that surveys covered around 3 (million) out of every 202 (million) people, or 1.5%. If the ACS surveyed approximately 1.5% of the 7,829 Math and Computer Science majors, the quartiles for income given in the report are based on surveys of around .015*7,829≈117 people. Of course, we don't know how many people they actually surveyed with this major, but this seems small. How large might the standard error be for the $98,000 median? Here come some back-of-the-envelope calculations! Watch out for LOTS of assumptions!

To simplify things, let us assume that the distribution of salaries for the majors is a normal distribution-- of course this is not true, but this is a rough calculation, after all (and doing a better job requires having the raw data!). Then, the $75,000 and $134,000 1st and 3rd quartiles would be around 0.67 standard deviations above and below the mean. These two numbers are 23 and 36 thousand dollars away from the median, respectively (providing evidence of non-normality!), so lets guess that 0.67 standard deviations is in the neighborhood of 30,000, making 1 standard deviation around 30/0.67 ≈$45,000.

Now, given that the distribution is not normally distributed, I would bet that the confidence interval would be even wider. I think that reports like this should give you a clue that some of their estimates have confidence intervals that are over $20,000 wide!I was told that in a Future, updated report which will merge the 2009 and 2010 ACS data, the CEW plans to issue some guidance about standard errors in an appendix. I think that reporting sample sizes for each major would largely satisfy my concerns.

Now, to be fair, I am picking on one of the less frequent majors and highest variation majors in the tables... most of them will be better than this. However, these reports should still at least MENTION that this is sample data, and the numbers are only estimates, and that comparing numbers across majors might be unwise due to errors. Additionally, these survey forms are typically filled out by one person in the household for all household members-- this introduces other forms of survey error into the mix. Ask yourself-- how accurately do I know what my spouse makes in a year? How many thousands might you be off if I asked you on the spot? For that matter, how well do you know your own? Or, how accurately would you report your own income? (Copies of the Survey forms can be found here)